What is Enterprise Information Management (EIM)
Enterprise information management (EIM) refers to the optimization, storage and processing of all data created and used by a large business through its day-to-day operations. Enterprise information management seeks to ensure that data is managed securely through its lifecycle and is accessible to the appropriate business processes when it is needed. EIM faces a number of challenges including the diversity of file formats, data stuck in legacy systems, and the general user experience. In addition to being part of the corporate drive for efficiency, EIM is part of the legal compliance for many firms as business information has specific requirements for retention and deletion. By virtue of handling sensitive personal information as part of doing business, many financial firms have necessarily been early adopters of enterprise information management.
BREAKING DOWN Enterprise Information Management (EIM)
Enterprise information management (EIM) is most often used as a universal label for the processes, policies and software solutions needed to manage data across a large business. For small operations with one location, a filing cabinet with a lock may be all the information management required. But a more comprehensive and customizable system is usually needed for a large company with branches and business lines spanning borders with different regulatory regimes for privacy and appropriate data use.
EIM and Data Protection
Nations and economic zones like the European Union (EU) have become more active in their regulation of data in the digital age. New regulations like the General Data Protection Regulation (GDPR) now require dedicated data protection officers (DPO) to set the retention periods and access rights within an organization for personal data. EIM has emerged as one possible compliance solution for these regulations.
Developing an EIM Framework
Companies must be able to overcome certain challenges when designing the framework for its EIM strategies including organizational challenges (where they are right now versus where they want to be), what kind of support data professionals have from company executives and how to deal with overall data management. In most cases, it’s not a one-size-fits-all approach. Instead, companies should be willing to apply best practices for their own approach.